Document Intelligence
Invoices, forms, contracts, statements and reports. We build AI pipelines that read them, pull out what matters, check it against your rules and send it where it needs to go.
The service
OCR turns an image into text. Document intelligence understands what that text means: which number is the invoice total, which clause sets the renewal date, which field on a form is missing.
Modern AI models handle layouts and formats that template-based tools cannot. We pair them with validation logic, cross-checks against your data and review queues so the output is dependable enough to use in real processes.
Teams type figures from PDFs and scans into systems, one field at a time.
Every supplier, client or partner sends documents in a different layout.
Missing or incorrect fields are discovered downstream, causing rework and delays.
Contracts and reports need review, but key details are buried in pages of text.
Key capabilities
Identify document types automatically and route each to the right process.
Pull structured fields, tables and line items from varied layouts.
Verify totals, dates and identifiers against business rules and your records.
Produce concise summaries and highlight key terms, obligations and risks.
Reviewers see the document beside extracted data and correct low-confidence fields.
Send validated data to your ERP, accounting, CRM or database.
Realistic use cases
Illustrative examples of how businesses apply this service. Outcomes depend on your process, data and scope.
Example workflow
Every document is classified, extracted, validated and reviewed when confidence is low.
01 · Trigger
Via email, upload, shared folder or scanner.
02 · AI step
Identify the type and extract fields and tables.
03 · Systems & tools
Check totals, formats and match against your records.
04 · Human checkpoint
A person confirms fields the system is unsure about.
05 · Outcome
Clean data flows into your systems with an audit trail.
Security & governance
Documents can be redacted, encrypted and retained according to your policies.
Each extracted field carries a confidence score that controls whether review is needed.
Original document, extracted values and any corrections are all retained and linked.
Model and storage locations can be chosen to suit your data residency needs.
Implementation approach
Collect representative samples of each document type, including messy ones.
Define the fields you need and the validation rules that apply.
Measure extraction accuracy per field on held-out samples before go-live.
Deploy with review queues, monitoring and continuous improvement from corrections.
FAQ
Common examples are invoices, receipts, purchase orders, bank statements, forms, contracts, reports and correspondence, including scanned and photographed documents. We confirm feasibility with your samples.
Accuracy depends on document quality and complexity. We measure it per field on your own samples before launch and use confidence thresholds so uncertain fields are reviewed.
Often, for clear handwriting, though accuracy is lower than for printed text. We test with your documents and route handwritten fields to review where needed.
We design storage to fit your requirements, including your own cloud account, retention limits and regional hosting.
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